Daasity

Unify omnichannel data, reduce manual reporting, and give teams actionable insights for more informed business decisions.

Create and activate relevant customer audiences to deliver more personalized campaigns, support retention, and find high-value customers for acquisition.

Unify sales reporting across channels so teams can identify growth trends and understand which products and channels drive revenue.

Helps brands identify which products and channels drive profitable growth and where to prioritize investment.

Understand which retail promotions deliver results and use performance and investment insights to plan future promotions more effectively.

Connect marketing investment and attribution to commerce results to assess channel performance, acquisition efficiency, and marketing’s relationship to sales and contribution.

Helps teams make smarter stock and replenishment decisions with visibility into weeks of supply, inventory risks, and sales velocity across products and locations.

Help CPG teams understand their market, identify growth opportunities, and prepare compelling, buyer-ready retail stories.

Connect AI applications to governed commerce data so teams can explore business performance with natural-language questions and trace answers to model definitions.

Get data strategy, customized analytics, hands-on platform support, and data operations tailored to your business needs.

Analysis of ecommerce sales, shopper behavior, product categories, marketplace pricing, and digital shelf visibility to guide retail performance and assortment decisions.

Products: Daasity platform, Omnichannel Sales Model, Syndicated Data + AI Analyst, Daasity MCP AI Server, Customization and consulting services

Connects revenue with product, channel, fulfillment, and marketing costs to measure contribution margins and identify drivers of profitability.

Products: Contribution Margin Model

Capabilities to measure campaign performance, attribution, customer segmentation, and dashboarding to optimize marketing ROI and decisions.

Products: Digital Marketing Mix, Daasity platform, Daasity Audiences

Analyzes inventory positions, sales velocity, and available forecasts to assess stock coverage, identify stock-out and overstock risks, and support replenishment decisions.

Products: Inventory Optimization model, Daasity platform

Evaluates retail promotional lift, trade investment, and account-level performance to improve promotional planning and returns.

Products: Retail Promotion Optimization

Daasity platform

Daasity is an omnichannel data and analytics platform for consumer brands. It integrates data from sales channels, advertising, marketing, retail, and other sources into a unified environment for reporting, analytics, and customer targeting. Teams can build custom dashboards and reports, access automated and continuously updated data, and send customer segments to marketing channels. The platform supports analysis across business performance, customer behavior, inventory, and product data, helping teams identify trends, forecast outcomes, and make informed decisions.

Category: Data Analytics Platforms

• Unify Data Across Channels
  Bring sales, retail, advertising, marketing, and other channel data together so teams can review business performance in a unified environment rather than across siloed sources.
• Create A Unified Data View
  Bring data from disparate systems into a shared environment so teams can access a more complete and consistent view of the business.
• Automate Recurring Reporting
  Reduce time spent pulling, updating, and preparing reports with continuously updated data and automated delivery of important business information.
• Tailor Reports To Your Business
  Create and refine dashboards and reports around business-specific metrics, channels, products, and analyses instead of relying only on fixed reporting.
• Analyze Business Performance
  Review connected business data across areas such as sales, marketing, products, customers, and inventory to understand performance and inform decisions.
• Activate Targeted Customer Segments
  Build customer groups from purchase behavior and send them to marketing channels to support tailored campaigns, advertising, and customer messaging.
• Customize Data To Fit Requirements
  Adapt models, definitions, and transformations to reflect the metrics and data requirements specific to a business.
• Forecast Trends And Outcomes
  Use business data to identify trends and forecast outcomes that can inform planning and decision-making.
• Align Teams Around Shared Metrics
  Give teams a shared view of standardized metrics and reporting periods to support consistent understanding of business performance.
• Present Performance To Investors
  Use investor dashboards to provide clear performance insights when presenting a business to potential funders.

Daasity Audiences

Daasity Audiences helps consumer brands turn customer data from sources such as sales, subscriptions, and reviews into targeted segments and lookalike audiences. Teams can choose ready-made segments or create custom groups, then automatically push them to marketing platforms including social media, email, and SMS for personalized campaigns. The tool also supports retention and acquisition efforts, identifies product pairings and upsell opportunities, and automatically keeps customer profiles and events up to date.

• Build Targeted Customer Groups
  Choose existing segments or create custom lists that reflect business needs, so teams can tailor campaigns and messaging to different customer groups.
• Activate Audiences Across Marketing Platforms
  Send customer segments to the marketing tools teams use to deliver targeted campaigns and personalized messages.
• Unify Customer Data
  Bring customer information from multiple channels into the audience workflow, supporting a broader view of customer behavior for segmentation and marketing.
• Find Similar High-Value Customers
  Build acquisition audiences based on high-value customers and use them to reach potential customers with similar characteristics on advertising platforms.
• Keep Customer Profiles Current
  Automatically update customer profiles and events to keep audience information up to date.
• Identify Product Pairings
  Discover products that are commonly paired and use those insights to shape personalized recommendations and upsell campaigns.

Omnichannel Sales Model

A licensed commercial intelligence model that provides a consistent view of sales across DTC, marketplaces, wholesale, and retail. It reports net sales and units by brand, product, channel, account, and retailer, and surfaces channel mix and growth trends. The model distinguishes retail sell-through from wholesale sell-in to support accurate revenue reporting and avoid double counting. Product, channel, account, sales-type, and ownership mappings are configured and validated for each customer. It can be deployed in a supported existing data environment or hosted on the Daasity platform.

• Compare Sales Across Channels
  Review sales and units across products, accounts, and channels in a consistent view to identify where revenue is coming from.
• Identify Channel Growth Trends
  Track changes in channel mix and growth over time to identify which channels and products are driving incremental growth.
• Align Teams Around Sales Metrics
  Give teams a shared basis for sales reporting through consistent metric definitions and documented business rules.
• Separate Sell-Through From Sell-In
  Distinguish retailer sales to consumers from brand sales to retailers, reducing the risk of double-counting revenue while retaining each measure for its relevant analysis.
• Configure Sales Rules For Your Business
  Adapt product, channel, and account mappings and sales rules to the customer's business, with implementation including source mapping, reconciliation, and validation.
• Deploy In Your Data Environment
  Use the model within a supported existing data environment or run it on the Daasity platform, with the deployment approach determined during solution design.

Contribution Margin Model

A licensed data model that connects sales and revenue to relevant product and channel costs, helping consumer brands understand contribution and profitability. It provides contribution margin tiers in dollars and percentages, profitability by product, SKU, channel, and account as supported by available inputs, and cost-driver breakdowns for items such as COGS, channel fees, fulfillment, marketing, and trade spend. CM1 and CM2 definitions, cost categories, and allocation rules are configured and validated for each customer. The model can be deployed in a supported customer data environment or hosted on the Daasity platform.

• Measure Contribution Across Margin Tiers
  See contribution margin in dollars and percentages, including CM1 and CM2, using definitions aligned to the business’s cost structure.
• Identify Costs That Affect Margin
  Examine relevant cost drivers alongside contribution to investigate how fees, fulfillment, marketing, and trade investments affect profitability.
• Compare Profitability Across Products And Channels
  Understand which products, SKUs, channels, and accounts contribute most after relevant costs, subject to the available data.
• Trace Revenue Through To Contribution
  Connect sales measures with relevant costs to see how revenue translates into contribution and investigate cases where revenue grows while margin falls.
• Prioritize Investment By Contribution
  Compare contribution after relevant costs to inform decisions about channel expansion, product priorities, promotions, and marketing or trade spend.
• Configure Costs To Match Your Business
  Align cost categories and allocation rules with the customer’s business and cost structure, with model definitions validated for each implementation.
• Align Teams Around Shared Definitions
  Give finance, sales, and marketing consistent metric definitions, and connect revenue and profit measures using shared product, channel, and account definitions when the models are used together.

Retail Promotion Optimization

A licensed data model that analyzes retail promotional lift, trade investment, and performance by account and product to inform future promotional plans. It compares promoted and non-promoted performance and uses promotion history to support planning. Key inputs include retail point-of-sale data, a promotion calendar, trade spend, and deductions.

• Compare Promotional Performance
  See how performance by account and product differs between promoted and non-promoted periods, providing a basis for evaluating promotional outcomes.
• Evaluate Trade Investment
  Connect trade investment and deductions with promotional results to assess the relationship between spending and retail performance.
• Measure Promotional Lift
  Compare baseline sales with incremental sales during promotional periods to understand the impact of promotional activity.
• Inform Future Promotion Plans
  Review historical promotion performance to inform future promotional planning and strategy.
• Optimize Promotion Returns
  Identify promotions that drive sales and use performance analysis to shape future strategies aimed at maximizing return on investment.

Digital Marketing Mix

A licensed data model that connects marketing investment, attribution, and commerce results to show how marketing performance relates to commercial outcomes. It reports spend, return on ad spend, and acquisition cost by channel and campaign, with attribution views across digital channels and marketing spend alongside sales and contribution. Key inputs include advertising platform spend, attribution or web analytics, and order data. The model covers marketing performance reporting and attribution; statistical marketing mix modeling needs are confirmed during scoping.

• Compare Channel And Campaign Efficiency
  Review spend, return on ad spend, and acquisition cost for individual channels and campaigns to understand their relative performance.
• Connect Spend To Commercial Results
  Compare marketing investment with sales and contribution to understand how spend relates to broader commercial performance.
• Trace Results Across Digital Channels
  Use channel-level attribution views to examine how digital marketing activity relates to commerce outcomes.
• Combine Marketing And Order Data
  Bring together advertising spend, attribution or web analytics, and order data as inputs for marketing performance reporting.

Inventory Optimization model

A licensable Daasity intelligence model that brings sales velocity, inventory positions, and available forecasts together to support stock and replenishment decisions. It provides weeks of supply by product and location, stock-out and overstock risk flags, and sales velocity in relation to inventory position. Inputs can include inventory positions from distribution centers, third-party logistics providers, and retail locations.

• Assess Stock Coverage
  View weeks of supply by product and location to support stock and replenishment decisions.
• Identify Stock-Out Risks
  Use stock-out risk flags to identify where inventory availability may need attention.
• Identify Overstock Risks
  Use overstock risk flags to identify where inventory may need review.
• Compare Sales And Inventory
  Bring sales velocity and inventory position together to help teams evaluate stock availability against product demand.
• Review Inventory Across Locations
  Include inventory positions from distribution centers, third-party logistics providers, and retail locations in the analysis.
• Incorporate Available Forecasts
  Use available forecasts alongside sales velocity and inventory position to support stock and replenishment decisions.

Syndicated Data + AI Analyst

A subscription solution for emerging and growth-stage CPG brands that combines syndicated market data from SPINS, NielsenIQ, and Circana with an AI Analyst. It helps teams understand category performance, market share, pricing, promotions, competitive benchmarks, and distribution opportunities. The AI Analyst highlights important trends and explains what they mean, while automatically generated retail narratives help teams present category momentum, brand performance, and expansion opportunities to retail buyers.

• Access Broader Market Data
  See what is happening across the full market, rather than relying only on data from within your own business.
• Surface Actionable Market Insights
  Focus on the trends that matter, understand their implications, and identify potential next moves without spending as much time interpreting disconnected charts and reports.
• Build Buyer-Ready Retail Stories
  Present a clear, compelling account of category performance, your brand’s position, and expansion opportunities without spending days gathering charts and assembling slides.
• Compare Category And Competitor Performance
  Understand how your brand and competitors are performing across the category, including how market share, pricing, and promotions compare.
• Identify Retail Growth Opportunities
  Find potential retailer and regional opportunities by examining distribution gaps and where the brand may have room to expand.

Daasity MCP AI Server

The Daasity MCP AI Server connects compatible enterprise AI applications, including ChatGPT and Claude, to Daasity’s governed commercial intelligence models. Teams can explore commerce performance using natural-language questions. Responses depend on connected data, governed metric definitions, model coverage, application configuration, and organizational architecture and permissions; responses should be validated before operational decisions.

• Connect Enterprise AI Tools
  Use compatible enterprise AI applications to interact with Daasity’s governed commercial intelligence models.
• Ask Questions In Natural Language
  Explore commercial performance with questions about business data, such as which channels gained revenue but lost contribution margin.
• Trace Answers To Governed Models
  Ground answers in governed definitions and trace figures back to the model. Connected data, model coverage, and application configuration affect the responses.

Customization and consulting services

Daasity’s professional services help brands plan and customize their data environment, analytics, and reporting around their business needs. The team provides strategy and analysis, acquisition and retention planning, merchandising analytics and forecasting, data culture and metric alignment, custom data models, integrations and visualizations, and managed platform support. Managed services include data refreshes, issue notification and resolution, integration of new platform features, and loading raw retail CSV files and spreadsheets into Daasity.

Category: Data and Analytics Consulting

• Align Data Strategy With Business Priorities
  Partner with Daasity to shape reporting and analysis strategies around long-term initiatives and specific business needs.
• Build Models Around Your Requirements
  Create data models suited to business needs and standardize metric definitions to match how the organization uses them.
• Refine Acquisition And Retention Strategies
  Use analysis of customer behavior and promotion performance to inform acquisition and retention marketing strategies.
• Improve Product And Inventory Decisions
  Compare product performance across sales channels and assess sell-through, inventory, margin, and results against plan to inform merchandising and forecasting.
• Align Teams Around Shared Metrics
  Develop a data dictionary and help teams use shared analytics definitions to support organizational alignment.
• Connect Sources For Accurate Reporting
  Get assistance setting up customized integrations for systems that need additional configuration, including ERPs, for reporting and analytics.
• Visualize Data To Match Your Needs
  Bring specific visualization ideas to life through tailored reporting formats, such as retail geo-heatmaps, RFM reports, and cohort analysis layouts.
• Keep Data Current And Resolve Issues
  Rely on the services team to manage data refreshes, provide notice when issues arise, and address them.
• Apply Platform Updates
  Have new Daasity features integrated into your account as they roll out, keeping accounts aligned with the latest Daasity functionality.
• Load Retail Data For Analysis
  Have raw retail CSV files and spreadsheets loaded into Daasity, making the data available for visualizations and analysis.